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Three Categories of Significant Inter-monthly Variations of the Warm Pool Convection in the Western Pacific and the Related Physical Mechanism
2020,25(2):113-124, DOI: 10.3878/j.issn.1006-9585.2019.19139
Abstract:On the basis of the observed outgoing longwave radiation (OLR) data and other reanalysis datasets during 1979–2018, three categories of significant inter-monthly variations of the warm pool convection in the western Pacific are identified. The first category shows a negative OLR anomaly in June and August and a positive OLR anomaly in July. By contrast, the second category shows an opposite OLR anomaly to the first category. Meanwhile, the third category shows a positive OLR anomaly in June and July and a negative OLR anomaly in August. All categories of inter-monthly variations are related to the ENSO background. The first and second categories occur in relatively weak La Niña years and El Niño developing years, which are closely associated with sea surface temperature (SST) anomaly in spring over the warm pool. When the SST is high in the preceding month, convection in the succeeding month is enhanced along with a reduced SST. Consequently, when the SST is low in the preceding month, convection in the succeeding month is suppressed along with an enhanced SST. The local air–sea interaction in the warm pool plays a key role in the first and second categories. Different from the two other categories, the third category occurs in El Niño decaying years, which is related to a high SST in spring over the tropical Indian Ocean. During June and July, convection near India is enhanced because of the high SST in the tropical Indian Ocean. Through the excitation of a Kelvin wave propagating eastward, convection in the warm pool is suppressed. In the meantime, the enhanced convection near India reduces the local SST and suppresses convection in August when the influence from the Indian Ocean on the warm pool convection is considerably weakened. By contrast, the warm pool SST in August tends to increase because of suppressed convection in June and July. As a result, the warm pool convection is enhanced in August. Therefore, the third category results from the combined effects of tropical Indian Ocean forcing and local air–sea interaction in the warm pool.
2020,25(2):125-138, DOI: 10.3878/j.issn.1006-9585.2019.19125
Abstract:A regional air quality model system driven by the weather research and forecasting model is applied to investigate the distribution and evolution of aerosol components in Beijing during the springs of 2014. The synoptic conditions, meteorological variables, and characteristics of aerosol chemical components are comparatively analyzed. Moreover, the effects of heterogeneous reactions on dust and anthropogenic aerosol surface on chemical compositions during the dust (17 Mar and 29 Mar 2014) and haze (25–27 Mar 2014) periods are quantified and compared. The comparison with the observations indicates that the model is capable of reproducing the meteorological variables, PM2.5, and PM10, and their chemical component concentrations during the study period. Moreover, the inclusion of heterogeneous reactions apparently improves the prediction accuracy of PM2.5 and chemical component concentration. In dust days, dust is the dominant component of PM10 mass (50.7%), and its percentage contribution to PM2.5 is comparable to that of organic material (OM) and primary particulate matter (PPM). In hazy days, nitrate (25.6%) and OM (23.6%) contribute the most to PM2.5 mass. Meanwhile, the fractions of nitrate, PPM, and OM in PM10 are comparable. The fraction of coarse particle considerably increases during dusty days, with the mean fraction of 45.5% in PM10. In hazy days, fine particle dominates the PM10 mass, with a fraction of 85.6%. The heterogeneous reactions increase sulfate and nitrate concentrations by 16.9% and 83.8% in dusty days and by 14.5% and 45.0% in hazy days, respectively. On an average, the heterogeneous reactions lead to changes in near-surface SO2, NO2, O3, sulfate, ammonium, and nitrate concentrations by -2.5%, -5.7%, -3.4%, 11.7%, 18.6%, and 58.5%, respectively, in Beijing during March 2014 thereby highlighting the important role of heterogeneous reactions in secondary aerosol formation.
Fine-Scale Structures of the Climatic Wind Environment within a Neighborhood Based on Large-Eddy Simulation
2020,25(2):139-152, DOI: 10.3878/j.issn.1006-9585.2019.18130
Abstract:Super-high-resolution numerical simulations on the wind environment in neighborhoods have been a hot research area in urban meteorology. In this study, a computational fluid dynamics model based on large-eddy simulation was utilized to simulate the climatic wind environment in Longhu Community in Chongqing, and the impacts of local building configurations on the fine-scale structures of the wind field was investigated. Results show that complex underlying surfaces played an important role in regulating local circulations. The strong winds were mainly found over open spaces and at broad streets parallel to the background inflow. The overall wind speed in summer was larger than that in other seasons and could reach a magnitude of 0.8 m/s. Different building configurations led to different patterns of local wind fields. The isolated tall building resulted in strong downward motions and winding flows at the windward side of the building, where strong winds frequently occurred. The scattered low buildings had little impact on the local inflow, resulting in a wind field with a homogeneous pattern. The densely built tall complex with an enclosing shape greatly blocked the wind, which led to a relatively weak wind speed in the vicinity and was unfavorable for pollutant dispersion.
2020,25(2):153-162, DOI: 10.3878/j.issn.1006-9585.2019.18158
Abstract:The influence of gradual external forcing changes on non-stationary system is significant, and the manner by which external forcing features are reconstructed from non-stationary system has become the key to study the dynamic characteristics of the system. In this study, a continuous system (the modified Lorenz system) is used as the reference model, based on the slow feature analysis (SFA). We discuss the ability of SFA in extracting different forcing signals in the model under conditions of periodic forcing, weakened periodic forcing, exponential decay forcing, and periodic forcing with exponential decay. Results show that the SFA method can extract external forcing information acting on the continuous system and its extraction effect is correlated to the intensity of the external forcing, noise, and embedding dimension m: The weaker the external forcing or the stronger the noise interference, the worse the extraction effect. Hence, the false high-frequency fluctuation appears in the extracted signal. The increase in embedding dimension m can improve the extraction effect of the external forcing signal to a certain extent. The results also shows that the external forcing acting on a single variable embeds its driving information in the system and SFA can extract the external forcing signal from other variables.
2020,25(2):163-171, DOI: 10.3878/j.issn.1006-9585.2019.18168
Abstract:Nowadays, dynamical climate models are inefficient in meeting the real needs of climate prediction. An effective method is the combination of dynamical and statistical models. This combination integrates large-scale circulation information from the dynamical models into the statistical model to improve the prediction skill. On the basis of the higher prediction skill for the large-scale summer circulation variable of climate models and the significant relationship between the preceding ENSO signal and summer precipitation in China, a hybrid statistical downscaling prediction method for summer precipitation anomaly prediction in China was proposed in this paper. Cross validation of seasonal prediction for summer precipitation in China was performed, and results showed that the downscaling method improved the multi-year average of anomaly correlation coefficient significantly. In real application, the average PS score reached 71.5/72.7 during 2013–2018/2015–2018, which is higher than that of the original model and the operational predictions issued by the Beijing Climate Center. This statistical downscaling model, which has stable predictive skill, is one of the effective references for operational seasonal prediction in China.
2020,25(2):172-184, DOI: 10.3878/j.issn.1006-9585.2019.19096
Abstract:Temperate grasslands are important components of terrestrial ecosystems. Investigating the grassland carbon exchange processes and their impact factors is essential to assess the variations in the carbon source–sink of terrestrial ecosystems and their responses to future climate change. On the basis of the eddy covariance measurements of carbon fluxes of meadow steppe at Tongyu during 2011–2017 and typical steppe at Maodeng during 2013–2017, the diurnal variation of carbon fluxes and its responses to environmental factors were analyzed. Results showed that both grasslands had the strongest carbon uptake in July. The monthly peaks of gross primary production (GPP), ecosystem respiration (Re), and net ecosystem exchange (NEE) of meadow steppe were greater than those of typical steppe. The diurnal variation of NEE was dominated by a unimodal pattern. However, when the saturated vapor pressure difference was high in July and August, GPP decreased around noon, leading to a bimodal pattern of NEE. Photosynthetically active radiation was the key factor in the diurnal variation of NEE of meadow steppe. Meanwhile, the diurnal variation of NEE of typical steppe was susceptible to shallow soil water content (5 cm). Water deficit led to a significant decrease in NEE at both grasslands. However, the meadow steppe carbon sequestration rate was more sensitive to water deficit than the typical steppe carbon sequestration rate. Meanwhile, water deficit modified the responses of GPP, Re, and NEE to temperature and photosynthetically active radiation.
Formation Mechanism of a Large-Scale Heavy Pollution Process in North China in Winter Based on Numerical Simulation and Statistical Fitting
2020,25(2):185-198, DOI: 10.3878/j.issn.1006-9585.2019.19006
Abstract:Using the WRF/Chem (Weather Research Forecasting/Chemistry) model, a large-scale PM2.5 heavy pollution process in northern China from 25 November to 2 December 2015 was simulated. Comparisons to observations show that the model can realistically capture the magnitude and variation of PM2.5 and meteorological factors, and can be used for the mechanism analysis of this pollution event. This paper further analyzed the mechanism of the strong pollution event from the aspects of dynamics, thermo-meteorological conditions, and chemical transformation. The results show that the dynamic factors mainly affect the pollution event through weakening of the surface wind and vertical wind shear. Thermal factors, such as a boundary layer inversion, promote the enhancement of the atmospheric stability, which is not conducive to pollutant diffusion. Based on the analysis of the PM2.5 composition, the nitrate, sulfate, and organic carbon content increased in this event, indicating that the secondary aerosol formation caused by vehicle exhaust and coal combustion contributes greatly to the PM2.5 pollution. To identify the main factors causing this pollution event, we used multiple linear regression and relative contribution rate accounting methods to quantify the multi-factor analysis. The results show that the thermal factors play a major role in the pollution process, with a variance contribution of 52%, dynamic factor of 34%, and a chemical transformation variance contribution of 14%, indicating that adverse meteorological conditions, especially thermal conditions, are the main causes of the pollution event.
2020,25(2):199-210, DOI: 10.3878/j.issn.1006-9585.2019.19008
Abstract:In this study, a heavy fog that occurred around the Bohai Sea on 17 December 2016, was investigated based on measurement data from microwave radiometer, wind profiler radar, four-component radiometer, sonic anemometer-thermometer, satellite images, buoys, conventional surface observation, and FNL (Final) reanalysis. The synoptic system for fog formation and vertical characteristics of radiation and turbulence were studied as key analysis points. The results show the following: (1) The fog appeared in the front of a low-pressure area and the back of a high-pressure area, and the warm-wet advection accompanied by strong low-level jet provided stable inversion and continuous water vapor accumulation in the fog area, which was very helpful to the fog formation. (2) The water vapor flux was closely related to the movement of the low-level jet. The growth rate of near-surface specific humidity was proportional to the intensity of the low-level jet. (3) Water vapor transport humidified the lower-boundary layer atmosphere around the Bohai Sea, which enhanced the attenuation effect of atmospheric radiation, leading to a decrease in short-wave radiation and an increase in long-wave radiation. When the fog formed, the net radiation was approaching zero. (4) Inversion effectively inhibited the development of turbulence. The kinetic energy and friction velocity of the turbulence were weak in the near-surface layer.
Impact of Different Planetary Boundary Layer Parameterization Schemes in the Regional Climate Model on Precipitation Simulation for Xinjiang
2020,25(2):211-224, DOI: 10.3878/j.issn.1006-9585.2019.19082
Abstract:NCEP-FNL datasets are used as the initial and boundary fields of the WRF model. Six planetary boundary layer parameterization schemes (PBLPS) are applied in the model for Xinjiang region with 10-km horizontal resolution. The spatial distribution and temporal evolution of the meteorological elements are analyzed. The analysis results show the following aspects: 1) The WRF model with six PBLPS can simulate the seasonal circulation of monthly precipitation and the spatial pattern of annual and rainy season precipitation. 2) For the Xinjiang region, the deviation of rainy season precipitation between the simulation conducted with the Grenier-Bretherton-McCaa (GBM) scheme and the observations is within ±30%. For the Tianshan area, the deviation of annual precipitation between the simulation conducted with the Bougeault-Lacarrere (BouLac) scheme and the observations is －19.13%. The TS scores of moderate and heavy rains are 0.37 and 0.33, respectively, in the test results of daily precipitation simulated with the GBM scheme. For the different types of underlying surfaces in the Tianshan area, the day and night precipitation can be well simulated by the model with the GBM scheme with the deviation of precipitation within 5 mm during long precipitation days. 3) The WRF model with the BouLac scheme can simulate the annual spatial and temporal distribution characteristics of annual precipitation in the Tianshan area, and the rainy seasonal precipitation can be well simulated by the model with the GBM scheme in Xinjiang. Therefore, PLBS with the WRF model in the Xinjiang region should be considered.
Volume 25,2020 Issue 2
Linear trends in high temperature and heatwave occurrence in China for the period 1960~2018: analysis method and results
Available online:January 19, 2020 DOI: 10.3878/j.issn.1006-9585.2019.19134
Abstract:High temperature and heatwave (HT and HW) directly impact human health and crop growth. Investigating the trends in the occurrence of HT and HW is one of the fundamental questions of climate change research and can provide valuable information for living and production. Most of the previous studies on trends in the occurrence of HT and HW used ordinary least squares (OLS) method to calculate the magnitude of linear trend and then used student’s t-test to determine the statistical significance of this trend. This study examined whether traditional methods are suitable for the trend estimation of the occurrence of HT and HW in China. By showing a case of the annual count of HT days with extremely excessive occurrences in 2018 at a station in northeastern China, we illustrated that OLS method is sensitive to outliers and can give spurious trend. Further, through normality testing and autocorrelation calculation, we found at least 91.14% of stations and 90.06% of grid boxes for the annual count of HT days and 92.18% of stations and 87.74% of grid boxes for the annual count of HW in China are non-Gaussian, and the majority of them have serial correlation. Applying a nonparametric method that is insensitive to outliers and takes into account serial correlation, we gave a more accurate estimation of the linear trends in the annual count of HT days and HW for every station and grid box, four typical regions average, and China area-average for the period 1960~2018. The results show that stations with statistically significant increasing trend in HT days occurred mainly in South China and northwestern China, and those in HW occurred nearly only in South China and several stations in Xinjiang Autonomous Region. In terms of area average of the trend in annual count of HT days and HW, only South China region and northwestern China region show statistically significant increasing trend, whereas North China and northeastern China not significant; those of China average are both significant. This study provides referential information for the choice of method in the estimation of trend and its statistical significance and in statistical prediction for HT days and HW.
Multi-timescale features for surface air temperature in the source region of the Yellow River during 1953-2017
Available online:November 05, 2019 DOI: 10.3878/j.issn.1006-9585.2019.19026
Abstract:Abstract: Based on the annual averaged surface air temperature data from eight meteorological stations in the source region of the Yellow River using the Ensemble Empirical Mode Decomposition (EEMD) approach, the multi-timescale temperature features of meteorological stations with Madoi as a representative during 1953-2017 and their contributions to the temperature variations are revealed. The correlations between different time-scale temperature oscillations with the SST indices are analyzed, particularly with the Atlantic Multidecadal Oscillation (AMO). The results demonstrated that: (1) a long-term temperature trend was 0.31℃/10a during 1953-2017 in the source region of the Yellow River, and the warming started in the late 1980s and accelerated in the late 1990s. (2) There were 3-year, 6-year, 11-year, 25-year, 64-year and 65-year quasi-cycle oscillations for the temperature during 1953-2017. Among them, the 3-year and 65-year quasi-cycle oscillations were significant. The amplitude of 3-year time-scale oscillation was large before the 21st century and decreased after the 21st century, while the amplitude of 65-year oscillation was enhanced after the 21st century. (3) The 3-year quasi-cycle oscillation occupied a dominant position during the period of 1953-1997, and the contribution of 65-year oscillation increased nearly five times which was equivalent to the contribution of the 3-year oscillation during the rapid warming period since 1998. (4) The correlations between temperature with Nino3.4 and PDO indices were not significant, but the maximum significant correlation was found when the temperature led PDO 22 years. Unlike PDO, the maximum significant correlation was found when AMO led the original temperature and its three inter-decadal components 0 and 3-7 years which supported that AMO had a significant impact on the temperature variation in the source region of the Yellow River. (5) The positive warm phase of AMO corresponded to the warming of the East Asia including China, and the source region of the Yellow River was only a part of that area. The negative cold phase of AMO from the early 1960s to the middle and late 1990s and the positive warm phase of AMO from the early 1990s to the present corresponded to the negative and positive phases of the temperature in the source region of the Yellow River. The AMO highly correlated with the 65-year oscillation. These results supported that AMO was an important climatic oscillation affecting the temperature variation especially on the inter-decadal time scales in the source region of the Yellow River.
Development of a Meteorology-Chemistry Two-Way Coupled Numerical Model (WRF-NAQPMS) and Its Application in a Severe Autumn Haze Simulation over the Beijing-Tianjin-Hebei Area, China
2014,19(2):153-163, DOI: 10.3878/j.issn.1006-9585.2014.13231
Abstract:An aerosol-optical module based on Mie scattering theory has been implemented in the Nested Air Quality Prediction Modeling System (NAQPMS), and a new coupler has been developed to deal with the interaction between the mesoscale meteorology model WRF (Weather Research and Forecasting Model) and NAQPMS. The one-way off-line and two-way coupled WRF-NAQPMS models are compared to simulate the severe haze in the Beijing-Tianjin-Hebei area from 27 September to 1 October 2013. The results show that the simulated meteorological elements and PM2.5 concentrations from the two-way coupled model with the aerosol direct radiation effect are more consistent with observations. During the haze period, the boundary layer meteorological elements change significantly because of the aerosol direct radiation effect over the Beijing-Tianjin-Hebei area: Incoming solar radiation is reduced by 25%, the 2-m temperature decreases by 1 ℃, the turbulent kinetic energy is reduced by 25%, the 10-m wind speed decreases by up to 0.2 m/s, and the planetary boundary layer (PBL) height is reduced by 25%. These changes make the atmospheric boundary layer more stable and further exacerbate air pollution over the areas where it is already severe, for example, the PM2.5 concentration increases by up to 30% over Shijiazhuang City. The analysis indicates that there is a positive feedback mechanism between haze and boundary layer meteorology, and the two-way coupled model incorporating this feedback is helpful for accurate simulation and forecasting of haze pollution processes.
2008,13(2):123-134, DOI: 10.3878/j.issn.1006-9585.2008.02.02
2010,15(4):337-353, DOI: 10.3878/j.issn.1006-9585.2010.04.01
Variations of the Sea Surface Temperature in the Offshore Area of China and Their Relationship with the East Asian Monsoon under the Global Warming
2011,16(1):94-104, DOI: 10.3878/j.issn.1006-9585.2011.01.09
Abstract:Based on the long time series of mean Sea Surface Temperature (SST) and high-resolution wind field reanalysis data such as HadISST and ERA-40 reanalysis data, the variations of the SST in the offshore area of China and their relationship with the East Asian Monsoon (EAM) in winter (December to the next February) and summer (June to August) are analyzed using the Empirical Orthogonal Function (EOF) and linear regression analysis methods. The results show that: 1) The SST in the offshore area of China in winter or summer exhibited significant interannual and interdecadal variations, and experienced a climate shift in the mid-1980s. The areas with the strongest increase in SST are located in the East China Sea (ECS) in winter and in the Yellow Sea in summer. The SST increased by 1.96°C in winter for the period of 1955-2005 and 1.10 °C in summer for the period of 1971-2006. 2）The EAM has displayed distinct interannual and interdecadal variations with a weakening trend since the end of the 1980s in winter, and since the end of the 1970s in summer. In addition, the linear regression analysis indicates the relationship of the SST to EAM in winter on interdecadal timescale is closer than that on interannual timescale. The interdecadal weakening trend of EAM in winter contributes to the rise in SST in the offshore areas of China, particularly significant in the ECS. Moreover, the related areas of winter or summer mean SST on the interannual timescale in the offshore area of China to the EAM are located in the South China Sea (SCS), and the relationship in winter is much more obvious than that in summer. It is found that the interannual variation of SST in the SCS has obvious relation to the anomalies of the meridional southward and northward winds over the SCS and zonal migration of the subtropical anticyclone over the western Pacific.
2006,11(1):14-32, DOI: 10.3878/j.issn.1006-9585.2006.01.02
2009,14(1):69-76, DOI: 10.3878/j.issn.1006-9585.2009.01.08
Abstract:作为酸雨和细粒子的前体物，SO2对空气质量和人体健康乃至气候与环境的影响十分重要，特别是在不利于扩散的气象条件下，SO2可造成城市短时间严重污染事件。作者以2006年北京325 m气象塔15 m观测平台SO2观测数据为基础，结合同步气象资料分析研究发现：1) SO2浓度冬季高、夏季低；全年日均值为(22.5±22.1)×10-9，最大日均值能达到113×10-9。日变化呈现双峰型，峰值出现在北京时间08:00和22:00；并且季节差异明显，冬季浓度为夏季的4.5倍，采暖期为非采暖期的3.2倍。2) 风向、风速与SO2扩散和输送密切相关，高浓度SO2在东北、东、西方向上出现频率分别为25.8%、13.8%和11.8%；而西北、北方向上的风速越大对SO2清除效果越好。3)利用平均晴空指数划分采暖期阴霾天和晴天，发现阴霾天混合层高度与平均风速仅为(376±204) m和1.1 m·s-1，容易造成SO2累积。4) SO2污染过程呈现周期性的局地累积—清除特征，地形、静风和暖低压是造成北京2006年1月一次重污染事件的成因。
2011,16(6):733-741, DOI: 10.3878/j.issn.1006-9585.2011.06.07
Abstract:A field performance of Doppler wind lidar Windcube (released by Leosphere Company) was conducted by Institute of Atmospheric Physics, Chinese Academy of Sciences (IAP/CAS) and Leosphere Company (from France) at the 325 m meteorological tower site (a part of IAP, located between 3rd North Ring Road and 4th North Ring Road) from 11 December to 14 December 2007. The intercomparison of wind speed and wind direction obtained by Windcube and wind cup anemometers (fixed in the meteorological tower) shows that：1) 10 min averaged wind speed is highly consistent between two types of wind data at six matched levels (63 m, 80 m, 100 m, 120 m, 160 m, and 200 m), the correlation coefficients all equal or exceed 0.98. 2) 10 min averaged wind direction is calculated with the vector method, the correlation coefficients of averaged wind direction at the six levels are 0.99. 3) In comparison with domestic Doppler wind lidar, Windcube performs slightly better in wind speed measuring, and equally well in wind direction measuring. The intercomparison indicates that Windcube is a reliable and swift mobile system mea suring wind profile at low levels.
The Mutual Response between Dynamical Core and Physical Parameterizations in Atmospheric General Circulation Models
2011,16(1):15-30, DOI: 10.3878/j.issn.1006-9585.2011.01.02
Abstract:A study of the interaction and mutual response between dynamical core and physical parameterizations by atmospheric general circulation models CAM3.1 and IAP AGCM4.0 is presented. Both the two models were integrated 60 d with ideal physics (Held-Suarez forcing) and with full physical package, respectively. The results show that the mutual responses between dynamical core and physical parameterizations are very different in the troposphere at low latitudes and high latitudes. In the tropical troposphere, the variability of temperature tendency due to dynamical core and that due to physical parameterizations are both large and have significant contributions to the variability of total temperature tendency, and they are in inverse correlation to compensate each other. In the polar middle and upper troposphere, the variability of total temperature tendency mainly relies on the tendency due to dynamical core, while the variation of temperature tendency due to physics is very slow, which can be seen as a stationary forcing. Unlike the tropical regions, there is a positive correlation between the temperature tendency due to dynamics and that due to physics in Polar regions. Moreover, the interactions and mutual responses between the individual physical parameterizations are also analyzed. The results show that the variation of temperature tendency due to moist process is the largest of all the physical parameterizations, and it contributes most to the total temperature tendency due to physics. The variation of temperature tendency due to long wave radiation is also large at high latitudes, while the variation of temperature tendency due to short wave radiation and that due to vertical diffusion are relatively small. There is a negative feedback between the cooling rate of long wave radiation and the heating rate of short wave radiation.
1999,4(1):98-103, DOI: 10.3878/j.issn.1006-9585.1999.01.21
2004,9(2):278-294, DOI: 10.3878/j.issn.1006-9585.2004.02.05
A Comparison of NCEP/NCAR, ERA-40 Reanalysis and Observational Data of Sensible Heat in Northwest China
2009,14(1):9-20, DOI: 10.3878/j.issn.1006-9585.2009.01.02
Simulation of Potential Vegetation Distribution and Estimation of Carbon Flux in China from 1981 to 1998 with LPJ Dynamic Global Vegetation Model
Abstract:The LPJ DGVM (Lund Potsdam Jena Dynamic Global Vegetation Model), which is a process based model, is used to simulate the vegetation distribution and estimate the interannual variation of net primary production (NPP), heterotrophic respiration (Rh) and net ecosystem production (NEP)in China from 1981 to 1998. It is shown that there are six main plant functional types (PFTs) besides the desert,that is tropical broadleaved evergreen tree, temperate broadleaved evergreen tree, temperate broadleaved summergreen tree, boreal needleleaved evergreen tree, boreal needleleaved summergreen tree and C3 perennial grass. In China, the total NPP varies between 2.91 Gt·a-1(C) (1982) and 3.37 Gt·a-1(C) (1990), increases by 0.025 Gt (C) average per year and has an increasing trend of 0.96%. The total Rh varies between 2.59 Gt·a-1(C) (1986) and 319 Gt·a-1(C)(1998), grows by 1.05% per year and by 0.025 Gt(C) per year. The linear trend of NPP and Rh for C3 perennial grass is more remarkable than those for other PFTs. The simulation of NEP is reasonable when the fire is brought in the model. Annual total NEP varies between -0.06 Gt·a-1(C)(1998)and 0.34 Gt·a-1(C)(1992). It is demonstrated that the terrestrial ecosystem is carbon sink in China. The above results are similar to those simulated by other models.
Variation Characteristics of the Sunshine Duration and Its Relationships with Temperature，Wind Speed，and Precipitation over Recent 59 Years in China
2011,16(3):389-398, DOI: 10.3878/j.issn.1006-9585.2011.03.14
Abstract:Using the data of sunshine duration, temperature, wind speed， and precipitation from 194 basic/reference stations over China from 1951 to 2009, according to the climatic division, the whole domain of China is classified into 11 climatic regions. The authors studied the changes in annual and seasonal trends of the sunshine duration by using linear trend analysis and Morlet wavelet analysis, and analyzed the characteristics between the sunshine duration and the temperature, the wind speed, and the precipitation. It was found that the annual sunshine duration showed a significant decreasing tendency during the recent 59 years with a decreasing rate of 36.9 h·(10 a)-1. The trend variations of the annual sunshine duration in 11 climatic regions were similar with that in the whole nation, only had the difference in degree. The sunshine duration of China changed from intensive to weak in 1981. There is an obvious 7－10-year periodic oscillation for the annual sunshine duration of China before the mid 1990s. The sunshine duration of the four seasons had a bigger decreasing amplitude in the coastal areas than in the inland areas, and in the South than in the North. There was a negative correlation between the annual sunshine duration and the temperature (correlation coefficient is -0.52), but a positive correlation between the annual sunshine duration and the wind speed (correlation coefficient is 0.76), and a negative correlation between the annual sunshine duration and the precipitation (correlation coefficient is -0.27). The first two correlation coefficients and the last correlation coefficient passed 99.9% and 95% confidence levels，respectively.
Cause and Anomalous Characteristics of the South China Sea Monsoon Trough Producing Heavy Rainfall in South China
2011,16(1):1-14, DOI: 10.3878/j.issn.1006-9585.2011.01.01
Abstract:Atmospheric processes associated with the South China Sea (SCS) monsoon trough which caused the heavy rainfall in pentad 3 of August 2007 in South China are analyzed using the reanalysis data of NCEP and satellite images. The results indicate that the Asian summer monsoon trough has independent space structure, convergence in the low layers and divergence in the high layers are in the south of the Asian summer monsoon trough. The climate analysis shows that both the Indian monsoon trough and the SCS monsoon trough reach their maximum in 〖JP2〗August. The SCS monsoon trough in pentad 3 of August 2007 was located in South China coastal areas and had strong intensity. The convergence in the low layers and divergence in the high layers were also stronger. The Indian monsoon trough was also stronger. The strengthened South Asian high locating over the Tibetan Plateau is the main cause for the strengthening of the Asian monsoon trough. The subtropical high in the western Pacific is located over Japan and is intensified, which is propitous to the northward 〖JP〗movement and the enhancing of the SCS monsoon and monsoon trough. The increased temperature over the Tibetan Plateau induces the stronger easterly in the upper levels, westerly in the low levels,and the enhancing convergence in the low layers and divergence in the high layers of the SCS monsoon trough. The long wave trough in the westerly belt is intensified and extends to Southwest China, which causes the SCS monsoon trough to become stronger. The SCS monsoon trough has an intraseasonal period. The intraseasonal oscillation has an important effect on the northward movement and enhancement of the SCS summer monsoon trough.
2011,16(1):47-59, DOI: 10.3878/j.issn.1006-9585.2011.01.05
Abstract:Based on the MODIS observations, the performance of Interactive Canopy Model(ICM), a dynamic vegetation model including the carbon and nitrogen cycles of the terrestrial ecosystem, has been assessed. The Leaf Area Index (LAI), a key parameter with seasonal variation in vegetation dynamics, is simulated by ICM and compared with the MODIS data. The results show that ICM can simulate the main characteristics of the seasonal LAI fluctuations. Compared to the observation, LAI is overestimated in high and low latitudes, but underestimated in middle latitudes by the model. The underestimation of the LAI in middle latitudes is followed by the vegetation sprout for the reason that the modeled growth is always slower than the observed one. The bimodal distributions for the tropical evergreen broadleaf trees and crops have not been well captured. In addition, the simulated results for the grassland are more reasonable than other Plant Function Types (PFTs). The results will provide important clues for the parameterization improvement and parameters optimization of the ICM.
Combination of Wavelet Decomposition and Least Square Support Vector Machine to Forcast Atmospheric Ozone Content Time Series
2010,15(3):295-302, DOI: 10.3878/j.issn.1006-9585.2010.03.09
Abstract:The atmosphere ozone content forecast model was established based on the combination of wavelet decomposition and advanced Least Square Support Vector Machine (LSSVM) regression. This can be approached in three steps: (1)The observations were decomposed into several different frequency signal subsets,(2)the independent prediction models of decomposed signals with Takens delay embedding theorem and Least-Squares Support Vector Machine (LSSVM) were set up, (3)independent predicted results were integrated as the final prediction with wavelet reconstruction. Application experiments with data from Xianghe and the other three observation stations show that the method can make better prediction effectively for the atmospheric ozone content, as compared with conventional Support Vector Machine(SVM) and Artificial Neural Network(ANN).
2008,13(1):75-83, DOI: 10.3878/j.issn.1006-9585.2008.01.10
A Research on the Application of Spatial Difference Method in Quality Control of Surface Meteorological Data
2010,15(3):229-236, DOI: 10.3878/j.issn.1006-9585.2010.03.02
Abstract:A new Quality Control（QC）technique called spatial difference method is introduced in detail and applied to spatial checking of some basic meteorological elements at seven representative stations in China for the year of 2007 in order to evaluate the applicability of this approach．The checking tests are conducted on ten basic meteorological elements including daily mean pressure，maximum pressure，minimum pressure，mean temperature，maximum temperature，minimum temperature，mean vapor pressure，mean surface temperature, maximum surface temperature, and minimum surface temperature．It is shown that this method works well in identifying errors of single meteorological element．As compared with spatial regression test on discriminating artificial errors，the spatial difference method is more effective．Furthermore，same as the other spatial checking methods，the distribution of neighboring weather stations should be concerned necessarily as influence factors．
2002,7(2):209-219, DOI: 10.3878/j.issn.1006-9585.2002.02.08
2010,15(5):541-550, DOI: 10.3878/j.issn.1006-9585.2010.05.02
Abstract:The Nested Air Quality Prediction Modeling System (NAQPMS) has been applied to the routine air quality forecast in Beijing during the Olympic Games. Monte Carlo method is used to analyze the uncertainty of ozone simulation of NAQPMS during the Olympic Games, from 8 to 24 Aug 2008. Latin hypercube sampling has been used for multi-variables sampling, and 50 ensemble runs have been made with 154 parameter uncertainties being considered together. By the temporal average, the most important parameter to the surface ozone output uncertainty in Beijing is the local precursor emissions during the day time. Other important factors include NO2 photolysis coefficient, wind direction, precursor emissions from the surrounding areas of Beijing, and vertical diffusion coefficient. The wind direction and precursor emissions from the surrounding areas of Beijing have the greatest impact on the uncertainty of daytime ozone simulation at higher levels (above about 150 m). The main uncertainty factors in ozone simulation at night are local NOx emissions and vertical diffusion coefficient. Given the predefined input uncertainties, the average uncertainty of ozone simulation is 19 ppb, ranging from 2 ppb to 49 ppb.
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Editor in chief: 李崇银